This document discusses using temporal analysis of satellite imagery to detect crop types early in the growing season. It analyzes images from May, July and August of 8,000 fields containing mainly corn and soybeans. Features like pixel values over time and weather data are engineered. A random forest model is able to detect crops with 24% error using images alone, which improves to 19% error when weather data is added, and further to 21% error using lasso regression and SMOTE to balance the data sets. The goal is to build a Python model and crop detector application that can identify crop types early in the growing season.

1. Temporal analysis of satellite imagery to determine crop type
Tatiana
Dashevskiy

2. 1 out of 3 farms use FarmLogs services

3. Fertilizer
Match Services for Specific Fields

4. Fertilizer
Crops only detected
at the END of seasonMatch Services for Specific Fields

5. How to Detect Crops Early in the Season
Temporal analysis of satellite images

6. Deliverable: Model in Python and Crop Detector
Application
https://youtu.be/EPtDwFKibOI

7. Features:
- Time Series Data
- RGB
- Near-infrared
- vegetation index
- Crop Type:
- 60% corn
- 40% 6 other crops
Image Data
May
July
August
8,000 Images for 900 Fields

8. Feature Engineering
May
July
August
Slope of Average pixel value over time per Field

9. Feature Engineering
May
July
August
Slope of Average pixel value over time per Field

10. Feature Engineering
May
July
August
Slope of Average pixel value over time per Field
Soybean
Corn

11. Images only
RGB, near infrared, vegetation index
24% Error
Random Forest
Crops detectable early in the season!

12. Images only
RGB, near infrared, vegetation index
24% Error
Weather
19% Error
Lasso regression analysis + SMOTE to
balance data sets
Random Forest
Crops detectable early in the season!
min & max temp, precipitation, etc.

13. Images only
RGB, near infrared, vegetation index
24% Error
Weather
19% Error
Lasso regression analysis + SMOTE to
balance data sets
Random Forest
Crops detectable early in the season!
min & max temp, precipitation, etc.
21%
Improvement!

14. Tatiana Dashevskiy
PhD in Physics, Applied dynamical systems in
neuroscience
Post Doc Seattle Children’s Research
Institute